A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth from defocus: a spatial domain approach
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Variational Approach to Recovering Depth From Defocused Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rational Filters for Passive Depth from Defocus
International Journal of Computer Vision
An MRF Model-Based Approach to Simultaneous Recovery of Depth and Restoration from Defocused Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth from Defocus vs. Stereo: How Different Really Are They?
International Journal of Computer Vision - Special issue on computer vision research at the Technion
Shape and Radiance Estimation from the Information-Divergence of Blurred Images
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Optimal Selection of Camera Parameters for Recovery of Depth from Defocused Images
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Depth Measurement by the Multi-Focus Camera
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
The Optimal Axial Interval in Estimating Depth from Defocus
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Geometric Approach to Shape from Defocus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two motion-blurred images are better than one
Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
Programmable aperture photography: multiplexed light field acquisition
ACM SIGGRAPH 2008 papers
Flexible Depth of Field Photography
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
International Journal of Computer Vision
4D frequency analysis of computational cameras for depth of field extension
ACM SIGGRAPH 2009 papers
Depth and deblurring from a spectrally-varying depth-of-field
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Optimized aperture shapes for depth estimation
Pattern Recognition Letters
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The classical approach to depth from defocus (DFD) uses lenses with circular apertures for image capturing. We show in this paper that the use of a circular aperture severely restricts the accuracy of DFD. We derive a criterion for evaluating a pair of apertures with respect to the precision of depth recovery. This criterion is optimized using a genetic algorithm and gradient descent search to arrive at a pair of high resolution apertures. These two coded apertures are found to complement each other in the scene frequencies they preserve. This property enables them to not only recover depth with greater fidelity but also obtain a high quality all-focused image from the two captured images. Extensive simulations as well as experiments on a variety of real scenes demonstrate the benefits of using the coded apertures over conventional circular apertures.